Rational drug design or the pathology of amyloid diseases are only two problems whose solution requires a detailed understanding of the relation between chemical composition and structure (and function) of proteins. The present project describes attempts to explore this relationship through computer simulations. The goal is to understand the folding and interaction of proteins solely from the physical forces between the atoms within a protein, and between the protein and the surrounding environment. Extending previous work and relying on algorithms developed in his group, the PI aims at deriving models that describe the fundamental processes of protein folding, aggregation and interaction in a cell. As an example, the PI will study in silico the mechanism by that two proteins, the 64- residue Chymotrypsin Inhibitor 2 and the 93-residue protein TOP7, fold into their specific shape. This is in itself a daring computational task that will require further algorithmic advances and implementation in massively parallel software. Simulating these molecules the PI will not push computer simulations beyond its present limits, and establish rules that describe folding in small proteins. Knowledge of such rules will pave the way to more efficient ways of drug design. In a second line of research the PI goes beyond single proteins and studies the interaction between multiple A chains and their subsequent oligomerization. He will investigate what factors favor oligomeric species over monomeric states, and the effect of point mutations and metal ions on the stability of the oligomers. As A aggregates are connected with the neuropathology of Alzheimer's disease this study will contribute to the developing understanding of the biogenesis of this disease. PUBLIC HEALTH RELEVANCE: Folding, Misfolding and Aggregation of Small Proteins Project Narrative Computer simulations are proposed to study the process by that proteins fold into their biologically active form, and the conditions under that these molecules misfold and subsequently aggregate. This will contribute to the developing understanding of the biogenesis of diseases related to misfolding and aggregation, and could lead to more efficient ways of drug design.